Single-cell immune profiling and TCR repertoire analysis

Visualization of transcriptomes of single CD4+ T cells pre-vaccination and tetramer-positive CD4+ cells post-vaccination in melanoma patients by t-distributed stochastic neighbor embedding (t-SNE; Ott and Hu et al Nature 2017)

Single-cell transcriptome sequencing (scRNA-seq)

Single-cell transcriptome analysis is a powerful method for dissecting the cell-type composition of a heterogeneous population. TIGL has developed and provides:

Experimental methods to analyze single cancer cells, single immune cells from tumor infiltrates, and single immune cells from peripheral blood, including droplet- and plate-based methods for scRNA-seq and targeted RNA analysis

Single-cell TCR sequencing (scTCR-seq)

The technology of single-cell sequencing of TCR transcripts provides paired ⍺- and β-chain information, enabling identification of which TCR binds to a particular antigen. TIGL has developed and provides:

scTCR-seq protocols for
- Single T cells flow sorted into 96- or 384-well plates
- Using droplet microfluidics to process larger numbers of T cells
Slide-TCR-seq
- Determines TCR clonotype sequences in tissue sections

Two dominant SHANK2 neoantigen-reactive TCRαβ clones (dark and light blue) were captured in a glioblastoma patient’s T cell lines from post-vaccination PBMC by IFNγ secretion assay, and were matched to post-vaccination TCRαβ sequences detected by bulk RNA sequencing (Keskin and Anandappa et al Nature 2018).

TCR repertoire analysis on RNA

Analysis of TCR repertoire data is an important element in trying to understand the role of TCR diversity in immune responses. TIGL has developed and provides:

A protocol that uses small amounts of RNA (100 pg to 100 ng) to determine ⍺, β, χ, and δ TCR repertoire distributions

Staff

Kenneth Livak, PhD, Technology Lead Scientist

Shuqiang Li, PhD, Technology Senior Scientist

McKayla Van Orden, Technology Research Technician

Tommy Janes, Technology Research Technician

Publications